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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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views in real time. Yet raw video and point-cloud streams are massive, wireless links are unreliable, and safety demands that information be both timely and trustworthy. IONIAN tackles this bottleneck
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and interpretation of results Supporting the analysis of multiple mitochondrial ‘omics datasets, such genomics, transcriptomics and clinical data Collaborating regularly with the team members and
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Mesoscale Convective Systems (MCSs); organized systems of deep convective cells that can span 100 kilometres and persist over multiple hours. In tropical South America, 40-60 % of the rainfall can be related
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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astronomy. We develop and operate commercial-quality, cloud-based software application and platform services used by 10s of thousands of researchers to manage their large–and growing–data management
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Multiple self-funded PhD positions are available in Modelling and Simulation (M&S). The project will aim to mature software repositories describing the biomechanics of the human brain. The M&S tools
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular